With the availability of high bandwidth communication channels, real time video communication systems are becoming more common. For example, a real time video system connecting Seattle and Sioux Falls enables a surgeon in Seattle to view heart surgery taking place in an operating room in Sioux Falls. A video camera in Sioux Falls captures and transmits the compressed video signal over a high bandwidth channel to Seattle. The video signal is decoded and displayed for viewing by the surgeon. In this scenario, the amount of detail in the displayed image depends on the resolution of the video camera, the bandwidth of the channel, and the power of the processor decoding and displaying the video.
A problem with this system is that a viewer of the video, the surgeon in the scenario just described, may desire to selectively increase the detail in an area of the displayed video. One solution to this problem is to have a separate camera and channel for transmitting an image of the desired area of detail. This solution introduces two problems. First, the solution is expensive, since a separate video system and channel for transmitting a separate high resolution image doubles the cost of capture, transport, and display of the desired image. Second, the transmitted high resolution image is not integrated with the original image, which leads to user interface problems on both ends of the communication channel.
In the low bandwidth world, real time video systems have been in use for many years. For example, real time video conference systems are in regular use in corporations and universities. In these organizations, video conference systems are used when it is important to have face-to-face communication between people located in different places, but travel is not practical. A problem with video conference systems is that the video is not sharp because the systems operate at low data rates. There are two traditional approaches to improving sharpness, but each has drawbacks. One approach is to reduce the number of pixels per frame in order to increase the number of bits available to encode each pixel. With this approach each pixel will look sharper, but each pixel will also correspond to a larger region of the image, which translates into reduced spatial resolution in the image. A second approach is to reduce the frame rate (frames per second) to increase the number of bits available to encode each individual frame. With this approach the individual images will be sharper, but perceptually, the motion will appear to be jerkier.
For these and other reasons there is a need for the present invention.